Prediction of the Wetting Behavior of Active and Hole-Transport Layers for Printed Flexible Electronic Devices Using Molecular Dynamics Simulations

Molecular dynamics (MD) simulations were used to predict the wetting behavior of materials typical of active and hole-transport layers in organic electronics by evaluating their contact angles and adhesion energies. The active layer (AL) here consists of a blend of poly­(3-hexyl­thiophene) and phenyl-C₆₁-butyric acid methyl ester (P3HT:PCBM), whereas the hole-transport layer (HTL) consists of a blend of poly­(3,4-ethylene­dioxy­thiophene) and poly­(styrene­sulfonate) (PEDOT:PSS). Simulations of the wetting of these surfaces by multiple solvents show that formamide, glycerol, and water droplet contact angle trends correlate with experimental values. However, droplet simulations on surfaces are computationally expensive and would be impractical for routine use in printed electronics and other applications. As an alternative, contact angle measurements can be related to adhesion energy, which can be calculated more quickly and easily from simulations and has been shown to correlate with contact angles. Calculations of adhesion energy for 16 different solvents were used to rapidly predict the wetting behavior of solvents on the AL and HTL surfaces. Among the tested solvents, pentane and hexane exhibit low and similar adhesion energy on both of the surfaces considered. This result suggests that among the tested solvents, pentane and hexane exhibit strong potential as orthogonal solvent in printing electronic materials onto HTL and AL materials. The simulation results further show that MD can accelerate the evaluation of processing parameters for printed electronics

Molecular Modeling of Interfaces between Hole Transport and Active Layers in Flexible Organic Electronic Devices

Molecular modeling methods are used to understand the interfacial properties between the hole-transport and active layers in organic photovoltaic (OPV) devices. The hole-transport layer (HTL) consists of a blend of poly­(styrene-sulfonate) and poly­(3,4-ethylenedioxythiophene) (PEDOT:PSS), whereas the active layer (AL) consists of a blend of poly­(3-hexylthiophene) and phenyl-C61-butyric acid methyl ester (P3HT:PCBM). Simulation results on the HTL confirm the interpenetrating lamellar structure with alternating PSS and PEDOT domains as observed in experiments. In addition, interfacial results show high PCBM interactions with the HTL, which result in PCBM migration to the HTL surface. The observed PCBM concentration profile is discussed from the perspective of attractive interactions, and it is shown that these interactions are governed by the side chain of PCBM. Calculations also suggest that OPV device performance could be improved by, for example, increasing the number of benzene rings and backbone −CH₂– groups in the PCBM side chain, which would be expected to reduce PCBM concentration at the HTL surface. The results yield important insights into molecular interactions associated with the HTL and AL interfaces that contribute to final device morphology and thus provide guidelines toward materials design approaches for optimized device performance

РП Спецсеминар Совр. проблемы биофизики, биологии и биотех-и 2015 с печатью

Silica nanostructures find applications in drug delivery, catalysis, and composites, however, understanding of the surface chemistry, aqueous interfaces, and biomolecule recognition remain difficult using current imaging techniques and spectroscopy. A silica force field is introduced that resolves numerous shortcomings of prior silica force fields over the last 30 years and reduces uncertainties in computed interfacial properties relative to experiment from several 100% to less than 5%. In addition, a silica surface model database is introduced for the full range of variable surface chemistry and pH (Q², Q³, Q⁴ environments with adjustable degree of ionization) that have shown to determine selective molecular recognition. The force field enables accurate computational predictions of aqueous interfacial properties of all types of silica, which is substantiated by extensive comparisons to experimental measurements. The parameters are integrated into multiple force fields for broad applicability to biomolecules, polymers, and inorganic materials (AMBER, CHARMM, COMPASS, CVFF, PCFF, INTERFACE force fields). We also explain mechanistic details of molecular adsorption of water vapor, as well as significant variations in the amount and dissociation depth of superficial cations at silica–water interfaces that correlate with ζ-potential measurements and create a wide range of aqueous environments for adsorption and self-assembly of complex molecules. The systematic analysis of binding conformations and adsorption free energies of distinct peptides to silica surfaces will be reported separately in a companion paper. The models aid to understand and design silica nanomaterials in 3D atomic resolution and are extendable to chemical reactions

Prediction of Specific Biomolecule Adsorption on Silica Surfaces as a Function of pH and Particle Size

Silica nanostructures are biologically available and find wide applications for drug delivery, catalysts, separation processes, and composites. However, specific adsorption of biomolecules on silica surfaces and control in biomimetic synthesis remain largely unpredictable. In this contribution, the variability and control of peptide adsorption on silica nanoparticle surfaces are explained as a function of pH, particle diameter, and peptide electrostatic charge using molecular dynamics simulations with the CHARMM-INTERFACE force field. Adsorption free energies and specific binding residues are analyzed in molecular detail, providing experimentally elusive, atomic-level information on the complex dynamics of aqueous electric double layers in contact with biological molecules. Tunable contributions to adsorption are described in the context of specific silica surface chemistry, including ion pairing, hydrogen bonds, hydrophobic interactions, and conformation effects. Remarkable agreement is found for computed peptide binding as a function of pH and particle size with respect to experimental adsorption isotherms and ζ-potentials. Representative surface models were built using characterization of the silica surfaces by transmission electron microscopy (TEM), scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET), thermalgravimetric analysis (TGA), ζ-potential, and surface titration measurements. The results show that the recently introduced interatomic potentials (Emami et al. <i>Chem. Mater.</i> <b>2014</b>, <i>26</i>, 2647) enable computational screening of a limitless number of silica interfaces to predict the binding of drugs, cell receptors, polymers, surfactants, and gases under realistic solution conditions at the scale of 1 to 100 nm. The highly specific binding outcomes underline the significance of the surface chemistry, pH, and topography

Chemistry of Aqueous Silica Nanoparticle Surfaces and the Mechanism of Selective Peptide Adsorption

Control over selective recognition of biomolecules on inorganic nanoparticles is a major challenge for the synthesis of new catalysts, functional carriers for therapeutics, and assembly of renewable biobased materials. We found low sequence similarity among sequences of peptides strongly attracted to amorphous silica nanoparticles of various size (15–450 nm) using combinatorial phage display methods. Characterization of the surface by acid base titrations and zeta potential measurements revealed that the acidity of the silica particles increased with larger particle size, corresponding to between 5% and 20% ionization of silanol groups at pH 7. The wide range of surface ionization results in the attraction of increasingly basic peptides to increasingly acidic nanoparticles, along with major changes in the aqueous interfacial layer as seen in molecular dynamics simulation. We identified the mechanism of peptide adsorption using binding assays, zeta potential measurements, IR spectra, and molecular simulations of the purified peptides (without phage) in contact with uniformly sized silica particles. Positively charged peptides are strongly attracted to anionic silica surfaces by ion pairing of protonated N-termini, Lys side chains, and Arg side chains with negatively charged siloxide groups. Further, attraction of the peptides to the surface involves hydrogen bonds between polar groups in the peptide with silanol and siloxide groups on the silica surface, as well as ion–dipole, dipole–dipole, and van-der-Waals interactions. Electrostatic attraction between peptides and particle surfaces is supported by neutralization of zeta potentials, an inverse correlation between the required peptide concentration for measurable adsorption and the peptide p<i>I</i>, and proximity of cationic groups to the surface in the computation. The importance of hydrogen bonds and polar interactions is supported by adsorption of noncationic peptides containing Ser, His, and Asp residues, including the formation of multilayers. We also demonstrate tuning of interfacial interactions using mutant peptides with an excellent correlation between adsorption measurements, zeta potentials, computed adsorption energies, and the proposed binding mechanism. Follow-on questions about the relation between peptide adsorption on silica nanoparticles and mineralization of silica from peptide-stabilized precursors are raised